Featured byRMIT Future Skills
Overview
Teaming up with the best in industry, the Future Skills courses lean into the future of work to deliver the best in structured, mentor-supported, 100% online education.
Why choose this course?
As the use of Artificial Intelligence continues to rise, so do the questions surrounding the ethicality of the technology. According to a recent study by IBM, executives ranking AI ethics as important jumped from less than 50% in 2018 to nearly 75% in 2021.
This Ethical AI course from RMIT University empowers learners to approach and apply ethical AI, teaching them to design and build models with fairness and limited bias. Students will gain ethical AI literacy skills, enabling more meaningful discussions across AI disciplines and applying ethical principles to their organisations.
This Ethics of Artificial Intelligence course will be delivered to you in partnership with Udacity, meaning you'll have access to both Udacity's learning and career services as well as RMIT Online's course enablement support through the Learner Success team.
Programme Structure
Courses included:
- AI Ethics for Organisations
- Identify Bias Towards Fairness
- Mitigating Bias Towards Fairness
- Transparency, Trust, & Explainability
- AI Ethics for Personalised Budget Prediction
Key information
Duration
- Part-time
- 1 months
- 6 hrs/week
Start dates & application deadlines
- StartingApply anytime.
Language
English
Delivered
Online
Campus Location
- Melbourne, Australia
Disciplines
Artificial Intelligence Ethics View 11 other Short Courses in Artificial Intelligence in AustraliaWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
For Ethical AI, students should have experience working with and/or knowledge of the following topics:
- Identify and articulate the popular use cases of AI systems in society, such as an autonomous vehicles, smart voice assistants, and robots
- Create a machine learning model, such as a linear or logistic regression model, naive Bayes classifier, or neural network using the scikit-learn framework.
- Perform basic data parsing and visualisation activities, including using pandas data frames and visualisations libraries such as matplotlib.
- Create efficient scripts using Python 3.7.6 or higher versions using variables, functions and common data types.
- Articulate fundamental concepts on AI lifecycle phases (e.g., training and deployment), the inputs to AI systems (e.g. image, text, tubular), and the outputs/results of a typical AI system (e.g, predictions, interferences).
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents681 AUD / full≈ 681 AUD / full -
Domestic Applies to you
Applies to youCitizens or residents681 AUD / full≈ 681 AUD / full
Funding
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